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POLITECNICO DI TORINO

CORSO LAUREA IN INGEGNERIA ENERGETICA E NUCLEARE

SPATIAL ENERGY PLANNING FOR THE ENERGY-WATER NEXUS IN

MOZAMBIQUE

RELATORE: PROF. PIERLUIGI LEONE

Tesi di laurea di

MARCO ALBERTO PALOMBO

Matr. 253704

Anno accademico 2019-2020

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INDEX

Introduction…………………………………………………………………………………………………………………………………..…5

1. BACKGROUND

1.2 Energy sector and electrification status………………………………………………………………………….……..9

1.3 Agriculture……………….…………………………………………………………………………………………………………10

2. THE SPATIAL ELECTRIFICATION TOOL (OnSSET)

2.1 Methodology………………………………………………………………………………………………………………….…….14

2.2 Limitations……………………………………………………………………………………………………………………..…….16

2.3 GIS-input data…………………………………………………………………………………………………………………..….17

2.4 non-GIS input data…………………………………………………………………………………………………………….…22

2.5 Results of the calibration………………………………………………………………………………………………………30

3. ELECTRIFICATION FOR THE RESIDENTIAL DEMAND

3.1 Energy demand…………………………………………………………………………………………………………………….31

3.2 Results………………………………………………………………………………………………………………………………….32

4. ADDING THE PUMPING ENERGY

4.1 Groundwater for irrigation…………… …………………………………………………………………………………..40

4.2 The yiel-gap closure scenario……………………………………………………………………………………………….41

4.3 Energy demand…………………………………………………………………………………………………………………….44

4.4 Results………………………………………………………………………………………………………………………………….47

5. CONCLUSION………………………………………………………………………………………………………………………………53

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ABSTRACT

Energy, water and food are the basic perquisites to ensure human well-being and sustainable

development. It is projected that in the near future growth of population, urbanization, changes in

life-style, as well as climate changes, will lead to an increase of the competiveness between food,

water and energy rosources.

For instance, today agriculture accounts for 70% of global water withdrawal and food chain is

responsible for 30% of global energy consumption. By 2050, water demand is projected to increase

by 55%, energy by 80% and food by 60%, mostly driven by developing countries.

In this contest, it is crucial to correctly manage natural resources, being aware of the indissoluble link

between them.

The aim of this analysis is to provide a geo-spatial assessment to discuss how the electricity requered

to pump groundwater for irrigation can effect the electrification process in Mozambique. The study

is performed by means of OnSSET, an open source optimization tool based on GIS data (Geographic

Information System) that has been developed by the division of Energy Systems Analysis of the KTH

Royal Institute of Technology in Stockholm.

They reason why Mozambique has been chosen as study country are:

1. It has one of the lowest electrification rate (27%) in the World.

2. It is reach in energy resources (both conventional and renewable).

3. It has a very high population growth rate (2%/year), that will lead to an increasing food

demand.

4. It has considerable amount of cultivated land that is still farmed without modern techniques

(such as irrigation) and that can be exploited both for internal demand and export.

5. It has one of the largest groundwater potential in Africa.

The irrigation groundwater demand is evaluated in a particular scenario called “closure-gap

scenario”, in which the gap between current and potential cropland yield (produced food per

cultivated land) is minimized, avoiding, at the same, time the groundwater deplention.

The OnSSET outputs consist of the optimum technology distribution, chosen between grid extension,

PV stand-alone, PV mini-grid, wind mini-grid, hydro mini-grid, that minimize the local LCoE’s. The

only-residential results will be compared to the case in which the pumping energy is added

considering different scenarios with different household energy tiers.

It comes out that solar stand-alone systems are a valid solution for a considerable portion of the

unelectrified rural population, where grid exension would not be affordable. As the rural

consumption grows, the national grid exension becomes more suitable, replacing part of the stand-

alone solutions.

The electricity required by the groundwater pumping is relatively low with respect to the only

residential demand (1-4%), but its distribution is sufficient to change the OnSSET outputs. The great

majority of the pumping energy is required in rural areas, with low population density and far away

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from the national grid. In this sites, PV and hydro mini-grids turn out to be the best solutions,

replacing the too expensive solar home systems.

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INTRODUCTION

In 2016 the number of people without access to electricity was estimated at 940 milion (WorldBank),

with a global electrification rate that have steadly increased from 1990 (71 %) to 2016 (87 %). Like so

much else, this is not uniformely widespread. High-income countries, in fact, are assumed to have

100% electrification rate, while in most of sub-saharian countries it is still unacceptably low and it

struggles to rise up, even because of the high population growth.

This is the case of sub-Saharan Africa, which counts more than 620 million people without access to

electricity services, and nearly 730 million people that rely on traditional fuels (firewood and

charcoal).

The largest part of the unelectrified population is located in rural areas, far away from the existing,

usually poorly developed grid network. Electrifying these areas is a challenging process and usually

requires significant investments, as well as technological and structural changes in energy systems.

In order to maximize impact, not only public and private investments need to increase, but they need

to be deployed in a cost-effective way.

The goal 7 (“affordable and clean enery”) of the “Agenda for Sustainable Development” envisions

universal access to modern, sustainable, cost effective and reliable energy services by 2030. There is

evidence that quality of life is strongly correlated to electrification. For instance, basic service like

illumination, can involve people to read in night time, leading to increased education. The use of TV,

radio, smartphones or other information channels result in reduction of isolation, as well as in

disaster risk mitigation. Refrigeration can improve health condition by means of food, medicine and

vaccines storing.

However, providing access in such services will not automatically result in economical growth. Several

studies show that electrification can produce economical benefits if a productive use of electricity is

inserted in a context in which economical develpment has already taken place.

Figure 1-electrification in the World (WorldBank)

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A possible productive use of electricity is rapresented by the groudwater pumping and irrigation, that

can lead to more effective exploitation of agricultural and labor resources and, then, to a structured

economical growth.

The Water-Food-Energy nexus

Electricity, water and food, lie at the hearth of the so-called “Water-Food-Energy Nexus” (WFE

nexus). These three aspects are indissolubly linked and predicted to significantly increase in the next

few decades. For instance, today agriculture accounts for 70% of water global withdrawal and food

chain is responsible for 30% of gloabl energy consumption. In Europe aproximately 43% of the fresh

water withdrawal is involved in power plant cooling and, more in general, 90% of the global generated

power is water-intensive. By 2050, global water demand is projected to increase by 55%, energy by

80% and food by 60%, mostly driven by developing countries. As demands grow, the competiveness between resources rises up. For instance, a large-scale

hydropower plant can provide electricity and can store water for irrigation purposes, but it might

happend at expense of down stream agro-ecological systems. In countries like India, China and

Pakistan the introduction of irrigation schemes based on groundwater has allowed these economies

to grow up fast, but, at the same time, it promote the deplention of aquifer and groundwater

storage.The food started to be vulnerable to the electricity prices, resulting in improving of the pumps

electrical efficiency.

These examples are useful to understand the strong link between different resources and why large-

scale planning should never ignore possible implications in other sectors.

The WFE nexus is a promising multi-sectorial methodology consisting in the assessment of current

and future pressure on natural and human resources, as well as interaction between different

sectors. The context analysis allows researchers to identify main issues and goals and try to figure out

how to handle them. In this way, it is possible to provide information in order to plan investments,

policies, reforms and infrastructures at large-scale level, without occurring in unwanted second

effects.

The WFE approach can be divided in three main working areas:

• evidence: it is the starting point of the assessment, in which the current status of the natural

resources, as well as the human pressure on them, are evaluated.

• scenario development: it can help to understand the effect of different policies and strategies.

Different scenarios can be compared and it is possible to extrapolate key and irrelevant fators.

• response options: it refers to planning investments, policies, incentives, legislation, business

models etc. Specific indicators have to be monitored to assess the effects of interventions in

the variuos sectors.

The main drawback of the nexus methodology is the complexity, that is typical of multi-sectorial

approaches.

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In this study the evidence consists in the fact that Mozambique has one of the highest groundwater

potential in the south-eastern Africa, as well as a great amount of cultivated land that are still rainfed

and that could strongly benefit of irrigation schemes. An efficient groundwater lifting could be easily

provided by electric pumps, but in Mozambique the great majority of rural smallholder farmers has

not electricity access.

The scenarios involved in this study will consider first the 100% electricity access for only residential

demand and, then, the addiction of the lifting energy. The irrigation groundwater demand is

evaluated in a particular scenario called “closure-gap scenario”, in which the gap between current

and potential cropland yield (produced food per cultivated land) is minimized and the groundwater

withdrawal occurs without the resource deplention.

For each scenario it will be discussed investmets cost, installed capacity and distribution of the most

cost effective technologies.

Figure 2-WFE nexus and related sustainable goals (IRENA)

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1. BACKGROUND

Mozambique is a low-income country in Southeast Africa with a population of 31.2 million (35

inhabitans per km2), 61.7 % of which located in rural areas (WorldPop).

Poverty is widely spread in the country, effecting 55% of the population, and only 51% of

Mozambicans can benefit of improved drinking water sources. The Human Development and Gender

Equality Index are one of the lowest in the World.

The public spent on health is about 3% of the GDP and only 21% of the Mozambicans has access to

adequate sanitation facilities. Malaria and AIDS, in fact, are concerning problem, as well as regular

outbreaks of colera.

Mozambique population and youth dependency ratio (0-14 aged people rapresent 45% of the

population in 2015) are rapidly growing (2%/year) and they are continuing to pose pressure on public

service and infrastructure. Like in many other developing countries, Mozambique urban rate is

increasing, but it is primarily due to natural urban population growth instead of migration from rural

areas (it accounts for only 12 % of the overall urban population growth).

There is a great difference in quality of life index within Mozambique. The south, which includes the

capital Maputo, is far richer and more developed than the north. Maputo attracts almost all of the

foreign investment, while the northern regions still rely entirely on rural activities. As a conseguence,

in the south infrastructure, agriculture and health care services are progressing but in the north this

is not happening. There is also a remarkable difference between rural and urban realities.

Figure 3-Mozambique

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Mozambican society and economy still bears the sign of the civil war fought between 1977 and 1992,

started 2 years later the independence from Portugal and ended with the fall of Sovietic Union

(thanks to the mediation of S. Egidio Community). In reality, fights have continued untill 2019, when

the will of undertake a peace path was formalized.

In march of the same year, Mozambique has suffered the effects of one of the deadliest tropical

cyclone recorded in the South-West Indian Ocean basin. The nothern and central part sustained the

worst damages, including severe flooding, landslides, power cuts and hundreds of thousands of

dispaced people, resulting in aproximately 800 milion $ damage.

Despite the difficulties, Mozambique has one of the African highest potential in terms of arable land,

water (as explained before), renewable energy, gas, coal and mineral resources. It is also located in a

strategical position, with strong markets in five neighbouring countries, that give it the opportunity

to become a leading African economy. Ensuring that all Mozambicans enjoy a share of that potential

may be the country's greatest challenge.

1.2 Energy sector and electrification status

The country is rich in fossil and renewable energy sources and has emerged as a regional energy hub.

It can boast 12 GW of hydropower potential (the highest among sub-Saharian countries), high solar

potential (GHI can reach 2200 kWh/y in Nothern Mozambique), as well as important gas reserves in

the Rovuma Basin and offshore in the Northern region of the country (700 bilion m3). Mozambique

also has world class reserves of coal, part of wich have sufficient quality to be exported.

The country’s vast energy resources are far in excess to satisfy domestic demand and the country is

also well positioned to engage in significant regional trade with South Africa, the country’s largest

purchaser of electricity. Despite that, the pro-capita primary energy consumption is among the

lowest in the World, estimated at 0.44 TEP in 2014 (World Bank), more than 5 times lower than the

italian value (2.48 TEP).

In the 2017 the overall electricity demand was 15,000 GWh, the majority of which was largely

generated hydropower (56%) and thermal power plants (42%).

Cahora Bassa Hydropower is the largest power generation company, in charge of operating the 2,075

MW Cahora Bassa Hydropower plant and the associated transmission system. The generation sector

is complemented by independent power producers, that has played an important role in

Mozambique’s generation capacity expansion since 2014.

Access to grid electricity has expanded more than three times in past 10 years through grid extension

and, among the 20 countries in the world with largest access deficit, Mozambique increased

electricity access at a rate faster than the average.

On the other hand, the transmission infrastructures limit to further development. In fact, there is no

internal connnection between the north, where electricity from Cahora Bassa comes from, and the

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south, where most of demand is. Power from Cahora Bassa, is then routed to the southern system

through the South Africa’s grid.

Besides, Mozambique transmission network lacks resilience and very high energy losses (29%), in

addiction to fragile economical condition of the national power company (Electricidade de

Moçambique). As a conseguence, about two-thirds of Mozambicans do not have access to electricity, which is below

the average for Sub-Saharan Africa and with a remarkable disparity between urban and rural.

Along with technical transmission network issue, many other barriers to rural electrification have

been identified:

• Scattered population.

• Lack of generation capacity.

• High investment cost and relatively low involvment of the private sector.

• Poverty and low household affordability.

• Inadeguate planning strategies, as well as policy support and monitoring.

• Lack of awereness of human and economical benefit of electrification.

• Unwillingness to change lifestyle.

There is also a declared intention to make a better use of renewable resources by means of off-grid

systems, displacing off-grid diesel generators that are condidered problematic under a tecnical,

ecnomical and enviromental point of view. Today the main options are pico/mini hydropower and

solar photovoiltaic systems.

Recently new players have started promoting the solar market develpment, providing high-quality

certified solar products with more flexible payment schemes.

Nevertheless, the price of these products is still not affordable for most of the population, except for

few consumers located in urban and peri-urban areas of large cities. The conseguence is that the

market is dominated by low-quality products, which are traded in informal (untaxed) markets, and

which has negatively affected the consumer confidence in solar solutions.

1.3 Agriculture

The 22 percent of Mozambique’s GDP is rapresented by the agricultural sector, which employs about

71 percent of the population and almost the totality of the poor and rural people.

Today this sector is dominated by smallholder farmers using family labour (97%), cultivating small

plots of land ranging between 0.5 to 1.5 hectare (average of 1.8 hectare). For this farmers agricultural

production is entirely rainfed and only a small group of them uses to sell their harvest in the local

markets.

The remaining part is mainly located in the Southern region, consisting of small/medium private

companies which can have access to credit and irrigation.

Mozambique has the largest, most accessible and fertile lands in the southern Africa. Natural

vegetation covers about 78% of the territory and 45% of the whole surface is suitable for agriculture.

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Moreover, its strategical position, between five neighboring countries and the Ocean, give the

Mozambique the opportunity to become a large food exporter.

For these reasons, improving agricultural productivity is now a top priority for the country's leaders.

Groundwater exploitation could help to achieve this goal but today, like in many other sub-Saharian

countries, groundwater remains the ultimate source of irrigation water when surface water have

been depleted. In Mozambique, in fact, only 0.54 % of the total area equipped for irrigation makes

use of groundwater (AQUASTAT, 2017).

The internal renewable groundwater resource is estimated at 17.0 billion m³/year, which is largely

higher than global Mozambique water demand (1.47 billion m³/year in 2015 ,70-80 % for agricultural

purpose).

In conlusion, the groundwater recharge is more than enough to sustain the current and future

agriculture demand (at country level) but its usage is still limitated to provide drinking water in large

urban and rural areas. Ensuring Mozambique to benefit of this huge potential will be challenging and

will require complementary infrastuctures, such as electrification services.

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2.THE SPATIAL ELECTRIFICATION TOOL (OnSSET)

OnSSET (Open Source Spatial Electrification Tool) is an open source optimization tool based on GIS

data (Geographic Information System) that has been developed by the division of Energy Systems

Analysis of the KTH Royal Institute of Technology in Stockholm. Its source code, documentation, and

example data can be found on the KTH-dESA GitHub (Python implementation), provided under an

Open Source Initiative MIT License.

To the current state, OnSSET has supported electrification efforts in many countries around the

World including Afghanistan, Nigeria, Ethiopia, Kenya, Tanzania, Madagascar and Benin as part of

joint collaboration with the World Bank and the United Nations. In addition, OnSSET has featured in

several publications including the World Energy Outlook in 2014, 2015 and 2017.

It is a high-level analysis tool for the assessment of the most cost effective way to electrifeid the

population of the study region, basing on the minimization of the levelized cost of electricity (LCoE),

defined as the ratio between the lifetime costs (investment and O & M) and the electricity generated.

For the off-grid technologies it evaluated with the formual below:

where:

It = investment cost.

Mt = O & M cost.

Ft = the cost of the fuel, that in this analysis it is not taken into account because non-renewable off-

grid technologieds (diesel generators) are not considered, for the reasons explained in section 1.2.2.

Et = electricity demand.

n = project lifetime.

r = discount rate, set to 7% in this study, which is the result of a short to long term analysis made by

TredingEconomics.

The grid LCoE is evaluated as the sum of the average LCoE of the national generation mix plus the

marginal LCoE related to the grid extention.

The country is divided into uniformly-sized grid cells (commonly ranging from 1x1 km to 10x10 km

depending on the input data resolution), each with unique characteristics that influence

electrification costs, such as energy renewable potential, population density, distance from the

existing and planned transmission network, etc.

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OnSSET outputs could help answer questions like:

• What is the most cost effective way to electrify the country population?

• What would it cost to provide universal electricity access and how does this cost change according

to different residential consumption?

•How much new installed power would that imply?

OnSSET code basis is flexible and modular and resolution of analysis, GIS input data, technology types

and costs can all be customized as needed. It is written in Python language and it takes advantages

of GIS deckstop applications, such as QGIS or ArcGIS.

In this analysis OnSSET has been implemented to identify the least-cost electrification options

between five different tecnologies:

• Grid intensification/extension.

• Mini grid systems powered by renewable sources (solar PV, wind turbines, small-scale

hydropower)

• Stand-alone systems (Solar home systems or solar kit)

The results consist in a spatial distribution of the most cost effective technologies with their relative

LCoE’s, as well as overall values like overall investment cost, overall new installed capacity, population

split in different tecnologies.

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2.1 METHODOLOGY

The Onsset modeling process can be diveded into six steps:

1. The GiS inputs are combined in the settlement table. Each row of the table corresponds to a cell,

whose various informaton (coordinates, population, elevation, GHI, etc.) are stored in the table

colums.

2. The calibration of the table is implemented. It consists in the determination of the current

electrification status and in the distinction between rural and urban cells, taking into account

the projected country’s overall population. This process is needed to couple national statistics

with the model’s geospatial data.

A cell’s electrification status is calculated by evaluating its population density, night-lights in

satellite images, distance from the nearest road and from the existing transmission network.

If a cell has bright night time lights, it only needs to have a high population or be close to the

grid or a road. If a cell has low night-time lights, it can only be considered electrified if it has

very high population, and is close to the grid or a road. The parameters that determine the

cutoffs for night-time lights, road and grid distances are iteratively adjusted until the final

population that is considered as electrified approximates the 2020 national statistic.

A similar iterative process is implemented to couple the future urban and rural cells status

with the national parameter wich accounts for the projected 2030 population and urban rate.

3. Once the imput settlement table is calibrated, OnSSET can run starting from the residential

energy consumption tiers. An electricity demand is assigned to each unelectrified cell and it

is possible to set different energy tiers for urban and rural cells.

4. The off-grid LCoE is evaluated in each cell for the different technology options. This process is relatively straightforward, using technology-specific parameters and geospatial data for solar, wind, and hydro power potential. The mini-grid LCoE is not evaluated by means of the grid exention algorithm, but considering a fixed distrution lines cost, which depends on the number of household per cell, the cell size and the cell peak power demand.

5. Grid LCoE’s calculation is the most complicated part and takes place in two steps. The first

step consists in assuming that all the cell already electrified are grid-tied and they are provided

with the national grid LCoE. In the second step, all cells that remain unelectrified are evaluated

for grid-extension with the condition that the addictional MV lines lenght required to connect

the unlectrified cell has to be lower than 50 km. This process is iterative and implements

optimal extension paths to minimize extension costs for all feasible cells. Each time a new cell

is identified for grid-extension, the grid effectively “reaches” that cell, making further

expansion cheaper for other nearby cells.

A penality function is used to consider the increase of grid extention cost based on particular

territorial features. It accounts for the added cost considering five categories with scores from

1 (least) to 5 (most). The following list contains these five categories and their weights:

proximity to the nearest road (5%) and substation (9%), category of land cover (39%),

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elevation (15%), and slope (32%). The Grid Penalty is capped at 1.25 for the least suitable

cells, increasing the costs of MV power lines stretching from the HV line to the cell by 25%.

6. The off-grid and grid LCoE’s are compared and the most cost effective tecnology is assigned

to each row (cell) of the settlement table. Then the non-GIS output are evaluated (overall

investment and capacity requirements, population spilt in different tecnologies).

The additional puping electricity is added at a cell level, assuming that is equally distribuited in each

cell household and, hence, added to the residential demand. This could not rapresent a limitation

since, at the time, the great mojority of farmers are smallholders that make use of family labour. By

the way, the agricultural intensification assumed in the closure-gap scenario may change this asset,

resulting in a more commercial schemes.

Figure 4-Conceptual Onsset scheme

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2.2 LIMITATIONS

Onsset is a large-scale modelling tool and, naturally, it has to consider a relatively simplistic evaluation

of many aspects. The major limitations are:

• Iterative process based on night-time lights, population, distance from grid and roads is

recognized to be not a very good tool to find electrification area with low consumption,

especially if they lack street lighting (rural areas).

• There is no power-flow study to complete the grid extention simulation.

• The model do not provide temporal considerations about the electrification process.

• Planned HV lines are considered as equal as existing transmission network, taking for granted

that they will be built.

• The quality of grid electricity is considered as good as the off-grid can offer. In many parts of

the developing world, where bulk power systems have been shown to be very unreliable, this

could not be true, to the point of negating the benefits of grid-connection.

• Onsset consider the only residential demand, which could not rapresent a limitation since, as

explained before, the agriculture is mostly practised at household level.

• Chossing between only two consumption tiers could be limitating.

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2.3 GIS INPUT DATA

Geographic Information Systems (GIS) are becoming more and more accesible and can provide a

range of location-specific information in a wide range of study field.

They are very useful to assest analysis for large-scale projects and allows the researchers to quickly

have a first idea of how and where tecnical, economical and computational efforts have to be spent.

The GIS based imput data involved in this analisys are raster and vector datasets. The first consists of

digital aerial photographs, imagery from satellites and digital pictures, each pixel of them stores

information about a specific feature. Vector data are points, lines and polygons that rapresents data

in a dimensionless form.

A spatial resolution of 0.05 degrees (approximately 6 km) is used, making the number of cells equal

to 27504, that is a good compromise between accuracy and computational effort.

2.3.1 Population distribution

Population density map is used in order to understand where population resides and where there is

potential residential demand.

Gridded population is a raster type dataset, whose grid values indicate the number of people in each

cell in 2020. Worldpop has developed gridded population layers for many countries around the World

at 100 m spatial resolution.The layer has been resampled to the selected resolution and then

calibrated to obtain the original overall population. Interpolation error is avoided, setting the cell

population to zero where there are less then six people.

As figure 5 shows, the majority of the population is not uniformely widespread but mostly

concentrated in southern coast, in the central corridor and in the rural regions of the north.

Figure 5-Population distribution, from 0 to 250,000 people per cell (6900 people/km2)

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23.46 milion of Mozambicans live within 50 km from the existing transmission network and this value

rise up to 26.29 if we consider also the grid that is planned to be built in the near future.

2.3.2 Night-Time Lights

Night-time light raster layer indicates light sources on the surface of the study region using satellite

imagery. Light pollution is one the most immediate and effective information to indentify electrified

regions, but, of course, it is not immune to mistakes, as explained in the next lines.

The Visible Infrared Imaging Radiometer Suite (VIIRS) dataset is available at 250 m spatial resolution

and provides a luminosity indicator (from 0 to 63) for each pixel.

As it can be seen from the figures, Mozambique is a quite low illuminated country if compared with

OECD nations. It is possible to locate the main cities: Maputo in the south, Beira and Tete in the

middle region and Nampula in the north.

Satellite images are taken at regular times at night and compared to isolate transient light sources.

As explained in the section 2.2, they can lead to inaccuraties. In fact, in rural areas, where there is

access but the consuption is low and street lighting lacks, it could under-represent electricity access.

This is called “bottom censoring” and occurs when light levels are low enough resulting in light to be

treated as transient.

Figure 6-Night-time lights over the coutry (left) and over Maputo (right)

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2.3.3 Renewable resources

In order to estimate le LCoE’s of stand-alone and minigrid solutions OnSSET makes use of three raster

layer rappresenting the local energy potential.

“Energydata.info” provides global horizzontal irradiance maps for a several countries with a 100m

spatial resolution. The dataset (expressed in KWh/m2/y) is used to estimate the validity of solar based

solutions, such as stand alone PV and PV minigrid. In the same way mean wind velocity at 10 m height

map allows OnSSET to evalutate the wind capacity factor and the generation potential of wind

turbines.

The hydropower minigrid are evaluated according to a point vector layer rappresenting the sites

where there are the condition to exploit hydropower potential. This estimation is based on digital

terrain analysis and hydrological modelling that provide data about head, discharge and potential

power in each site. The cells are considered suitable for hydropower exploitation if they are located

whitin 10 km from the hydro-power point.

According to the hydro-point vector layer, in Mozambique the average head of the hydropewer sites

is 13 m and the average hydropower potential is aproximately 1.4 MW.

Figure 7-GHI, 10m height wind mean velocity, hydro-power potential

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2.3.4 Territorial characteristics

A specif raster layer (figure 9) provides information about the Mozambique land cover. It

distinguishes 17 different land covers, such as water bodies, grasslands, savannas, build-up zones,

cropelands etc.

78% of the territory is covedered with natural vegetations (in particular decidous broadleaf forest)

and 45% are rapresented by arable land. The main croplands are located in the southern part of the

country and, in the north, the small family farmlands merge with the natural vegetation. There is also

a considerable expanse of open shrublands in the inland of the country.

Two other raster layers (figure 10) aim to provide information about the elevation and the slope of

the Mozambique territory and are used, together with the land cover vector, to quantify the grid

Figure 8-Landcover raster

Figure 9-elevation and slope rasters

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extention cost increase due to inconvenient land condition, according to the penalty factor for the

grid extention, as explained in section 2.1

2.3.5 Infrastructures

Main roads, planned and existing electric transmission network and electrical substations are

involved by means of four different vector layers. These information, concurrently with the night-

time lights layer, are used in order to estabilish if the cell is already alectrified and to distinct urban

from rural areas. In the grid extention algorithm the planned transmission network is considered as

equal as existing grid.

Figure 10-Infrastructures layer

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2.4 NON-GIS INPUT DATA

In order to run the OnSSET, techno-econimic and demographic input parameters are used to

estimated LCoE’s and to calibrate the starting settlement table.

2.4.1 Demographic parameters

The current population of Mozambique counts 31.2 milion people and it is forecasted to reach 41.2

milion in 10 years (WorldPop). OnSSET estimates the electrical demand on the base of future

population and of the average household size, which in Mozambique is 4.4 people for rural areas and

3.7 for urban areas. In the table below Mozambican demographic inputs are listed:

table 1-demographic parameter

As said in the introduction, Mozambique urban rate is increasing at a lower pace with respect to other

sub-Saharian countries and it is mainly effected by natural urban popultion growth rather than

migration from rural areas.

2.4.2 Technological parameters

Technological parameters rapresent the most challenging non-gis inputs, because they are referred

to the short-medium period and they reflect a fluid and a uncertain setting that is typical of

developing countries. For this reason, similar project in simalar backgrounds are considered, making

assumptions as likely as possible.

2.4.2.1 Grid

As explained in section 1.2.2, the national power network is supplied by Electricidade de Moçambique

(EdM) and by Cahora Bassa hydropower company which are in charge of generation, transmission

and distribution. Power transmission is rapresenting a critical issue for the country for several factors:

• not prospereous macroeconomical and power market situation.

• retail tariffs do not recover the cost of power generation and distribution.

• capital expenditures for rehabilitation of the grid are not adequately funded.

• weak link between the northern of the country, where Cahora Bassa hydropower plant is

located, and the southern region, where most the electricity demand is.

• Cahora Bassa hydropower first sells electricity to Eskom (the South Africa electricity public

utility), which in turn sells the power back to southern Mozambique at an increased price.

• high electricity losses, estimated at 29.8%.

population 2020

population 2030

rural HH size

urban HH size

urban ratio 2020

urban ratio 2030

electrification rate 2020

unit people people people people % % %

value 31.2 M 41.2 M 4.4 3.7 38.3 44.2 27

23

In this study the grid weakness is ignored, considering the willingness of the Mozambique

government to enhance this issue by way of the costruction of the planned transmission line (figure

10). It is also declared that the energy losses will be reduced from 29% to 19% by 2023 and, in the

same way, this value is used in the model.

The capacity investment is the cost per unit power needed to increase the grid generation capacity

and the grid price is the LCOE of the grid-generated kWh. Both parameters are estimated according

to the projected generation mix, coming from TEMBA (The Electricity Model Base for Africa), an open

source model initially developed for the World Energy Outlook 2014.

Mozambique has one of the highest african hydropower potential and in the next future it will further

increase its exploitation. Installed power fed by biomass and coal is expected to be constant, reducing

their share.

As a result, the new grid installed power investment is set to 2250 $/Kw, which is the averge of the

mix generation over the next 10 years.

A similar methodology is applied to evaluate the LCoE of the grid-generating KWh and the result is

0.10 $/kwh.

SHARE SHARE SHARE

LCOE ($/kwh) 2018 2023 2030

BIOMASS 0.08 0.00 0.13 0.10

COAL 0.12 0.11 0.14 0.10

GAS 0.08 0.15 0.09 0.07

HYDRO 0.10 0.74 0.64 0.69

WIND 0.03 0.00 0.00 0.05

Table 2-World average LCoE’s and their share in Mozambique generated electricity (TEMBA)

Figure 11-Projected generation mix and capacity investments (TEMBA)

2020 2023 2030 2035

BIOMASS 4447 4412.5 4332 4105

COAL 2080 2080 2080 2080

GAS 1021 1021 1021 1021

HYDRO 1777 1788.4 1815 1929

WIND 1940 1906.7 1829 1743

capital investment ($/Kw)

24

The high large-scale hydropower share makes the grid LCoE slighty higher with respect to other

similar countries, in which it can be lower than 0.05 $/KWh. As explained in section 2.1, this value is

the starting point to evaluate the exented grid LCoE, adding the marginal deriving from transmission

and distribution network.

The base to peak ratio parameter rapresents the ratio between the average consumption over the

8760 hours of the year and power pick. Onsset is implemented to model only the residential

consumption and a typical tier 3 household consumption, able to support 4 led lights, 2 phone

charger, 1 radio and 1 medium-size TV, has a base to peak ratio of 0.5.

Table 3- Grid parameters

The cost of the grid extention depends on several parameters that are as important as hard to assess.

In this study they are based on previous studies in others rural areas of Africa. The imput used in this

analysis are presented in the following table:

Table 4- grid specific cost

Since there are not specific studies refering to the cost of HV/MV/LV lines in Mozambiqure, the only

way is to compare the OnSSET results to existing papers that deal with the cost of electrification in a

more general form. According to “The cost of providing electricity to Africa” (Orvika Rosnes, Haakon

Vennemo), this cost is estimated at about 500 $ per urban household. Concernig the rural

households, the connection cost ranges between 550 and 4300 $ in Tanzania and it is aproximately

2000 $ in Mozambique and Zambia.

losses Grid capacty investment grid price Base to peak ratio max grid extention

unit % $/kW $/kWh % km

value 19 2250 0.10 50 50

HV line MV line LV line Transformer

unit $/km $/km $/km $/unit

value 53000 7000 4250 4250

25

2.4.2.2 Off-grid

Off-grid technologies are a valid solutions where it is not possible or not convenient to grid-connect

an household. In this analysis stand-alone PV and solar/wind/hydropower minigrid are considered.

Stand-Alone PV

Solar home systems in Africa are small systems, with typical capacities of 20 W to 100 W, that provide

off-grid electricity services.

There is a substantial difference in scale and configuration with respect to OECD countries, where

small-scale solar rooftop systems are almost always grid-connected and range between 1 kW and 5

kW (10-250 higher than the typical African systems).

They usally provide only DC power, with no need for an inverter but requiring an expensive battery

for nighttime use. This DC system directly powers the system’s electrical load, generally highly

efficient LED lights and/or other small DC-powered appliances, such as radios, televisions, mobile

phone charging ports and USB chargers.

In the recent years the off-grid solar market has been developing thanks to the support of 25

small/medium business that are active or have an interest to enter in the market in the near future.

They typically purchase basic solar products that meet the Lighting Global Quality Standard at an

average price of 126 $.

At the same time, the market is dominated by the so-called informal traders, which sell low quality

products mostly coming from China, Tanzania and South Africa, avoiding to pay taxes. It is common

that people living in rural areas buy basic solar kits at half of the “formal” price without receving

warranty nor assistance.

OnSSET estimates the cost of the stand-alone PV starting from the specific capacity investment

(expressed in $/KW); than it evaluates the required capacity considering the electricity peak demand

and the capacity factor, which reflects the solar potential of each cell.

This methodology is typical of OECD PV rooftop systems that, as said before, are very different in

terms of size and configuration and it is hardly implemeted when the size of the systems is not

customable and of the order of few tens of Watts.

For these reasons i chose to assess and compare two cases:

1. The stand-alone PV systems are solar kits, like those purchased in informal traders. In this

case the solar potential is not considered and the installed capacity is fixed with respect to

the specific solar kit. The available solar kits are based on the local informal market but their

price are doubled in order to ideally provide quality certification, warranty and payment of

taxes.

26

the figures 12 shows a typical solar market in Maputo with its typical products and prices.

The device 2, for example, can provide electricity to run 3 LED lights, 1 phone charger and 1 radio.

device informal price ($) formal price ($)

2 51 102

4 739 1478

Table 5- Solar kit price

2. The PV installed capacity is estimated according to the conventional OnSSET method,

considering first the electricity peak demand and then the capacity factor. In this case the

stand-alone price is expressed in terms of USD per installed kW.

In this analysis i will refer to the typical african PV system price, that can vary in a very wide

range (6000-14000 $/kW), according to the IRENA 2016 dataset.

Figure 12-informal markets in Maputo, 1MZN = 0.013 $ (ECA, GREENLIGHT, “Off-Grid Solar Market

Assessment in Mozambique”)

27

First, i will consider the average price for pico-solar and sub-1kW systems (11250 $/kW and 9975

$/kW) and then i will make the price vary in the whole range.

PV mini-grid

According to 6 existing african mini-grids with a 100% solar fraction, objects of ESMAP’s study, the

average capacity investment cost is 8362 $/KW and the distribution accounts for the 24% of the total

cost.

country PV size (KW) CAPEX ($) distribution cost (% of CAPEX) investment cost ($/KW)

Chad 40 296529 26 7413

Tanzania 16 265312 12 16582

Nigeria 100 639212 40 6392

Liberia 23 151969 24 6607

Zambia 60 602757 29 10046

Sierra Leone 128 400703 15 3130

Table 6- Solar mini-grid projects in Africa (ESMAP)

The capital investment parameter should not include the compenents used for distribuiting

electricity, because they are already taken into account by OnSSET.

Figure 13-Per Watt investment cost of small SHS in africa, IRENA renewable cost database (2016)

28

Looking at the recent past, the costs of key mini grid components fell 62–85 percent between 2010

and 2018, due to the diffusion of utility-scale solar PV parks and of the deployment of rooftop solar

home systems. In the same way, the cost of lithium-ion batteries fell by 85 percent, driven by the

increased use of batteries in electric vehicles and utility-scale storage projects. The reduction in the

cost of energy management systems, the ever-increasing computing power of power electronics and

chips, and the decline in their cost, have contributed to the decrising of the capital investment as

well.

If the prices of mini grid components will decline by the same proportion by 2030, the upfront capital

cost of a solar mini grid would fall by almost 22 percent.

Under these considerations the capital investment cost of PV mini-grid is set to 4957 $/KW.

Hydropower mini-grid

Small-scale hydro is a very suitable option for rural electrification in Mozambique, which can boast

one of the gratest hydropower potential (12 GW) in sub-Saharian Africa.

Its investment cost can vary significantly depending on the site, size, and the cost of local labour and

materials.

The total installed cost for large-scale hydropower projects typically range from 1000$/kW to

USD 3,500$/kW, but it is not unusual to find projects with costs outside this range.

For instance, exploiting an existing dam that was built for other purposes may have costs as low as

500$/kW, but projects at remote sites, without local infrastructure and located far from existing

transmission networks, can cost much more than 3,500 $/kW.

Small projects have investment costs in higher range due to economy of scale.

Figure 14-Hydropower capacity investment (IRENA)

29

According to the hydro-point vector layer, in Mozambique the average head of the hydropewer sites

is 13 m and the average hydropower potential is aproximately 1.4 MW.

On the base of that, and using the hydropower IRENA database, the capacity investment cost has

been set to 3500 $/kW.

On-shore wind mini-grid

Today the installed cost of wind power projects is currently in the range of 1 700 $/kW to 2150 $/kW

for onshore wind farms in developed countries. There are considerable economies of scale in wind

power developments, as projects under 5 MW have significantly higher total installed costs than

larger systems. For example, In Mozambique the 0.3 MW pilot Inhambane project cost the equivalent

of about 5000 $/Kw. Moreover, it has been observed that in many countries the costs per unit of

planned project are higher then the unit cost of completed pilots.

In this analysis the capital investment cost is set to 5000 $/kW on the base of the only small-scale

project in Mozambique.

30

2.5 RESULTS OF THE CALIBRATION

The first part of the analysis consists in the assesment of the already electrified cells and the

distinction between rural and urban cells, as explained in section 2.1:

As figure 15 shows, urban population is concentrated in a few provinces: Maputo Province and

Maputo City (in the south), Sofala and Manica (in Mozambique’s central corridor) Nampula and

Ligonha (in the north). The urban cells cover 2.8% of the whole territory and host 44.2 % of the 2030

population.

The electrified population is mostly concentrated in urban areas, near the existing trasmission

network. In particular, the electrification rate results to be 68.3% for urban population and 1.2 % in

rural areas. The rural electrification seems to be slightly lower than the national statistic (4-6%). This

is due to the “botton censoring” effect concerning the nigh-time lights raster layer (setcion 2.3.2),

that tends to classify low rural lights as transient light sources, especially where street lighting lacks.

As expected, a key factor is rapresented by the distance from the existing transmission network:

Table 7- electrification status as a function of grid distance

Starting from 10 km from the existing transmission network, there is a significant drop in the

electrification rate, that continues to decrease with the distance from the grid with a lower pace.

Distance from existing grid (km) <5 5-10 10-20 20-50 >50

Electrification rate (%) 62.9 40.0 7.0 5.5 4.7

Unelectrified population (milion) 3.25 2.48 3.58 5.99 7.39

Figure 15-results of calibration

31

3. ELECTRIFICATION FOR THE RESIDENTIAL DEMAND

In this chapter the results of the analysis are presented considering only the residential demand.

3.1 ENERGY DEMAND

The result of the analysis is presented for two residential electricity demand options:

-Tier 1 consumption: the household can support basic electrical devices (3 LED lights, 1 phone

charger, and 1 radio) with a resulting 30 kWh/y.

-Tier 3 consumption: the household can support a more advanced alectrification (5 LED lights, 3

phone-charger, 1 radio, 1 medium size LCD television and one 100 lt fridge) with a resulting 410

kWh/y.

Onsset allows one to set different electricity demand for urban and rural households. In this analysis

two scenarios will be considered:

-Tier 1-3 scenario, in which urban population are supported to make use of Tier 3 consumption, while

rural are provided with Tier 1 consumpion.

-Tier 3-3 scenario, in which more effert are involved in order to provide Tier 3 consumption option

also to rural households.

In the figure 17 the geographical distributions of electrical demand are presented:

Figure 16-addictional residential demand distribution in tier 3-1 scenario (left) and tier 3-3 scenario (right), ranging from 0 to 14.5 GWh/y/cell

32

The overall electricity demand are respectively 1275.0 GWh/y and 3228.5 GWh/y. In the first scenario

the majority of new electricity requirement (88.3 %) comes from urban areas. This values decreases

to 34.8 % in the second scenario, where the large unelectrified rural population in the northern

Mozambique makes the demand more widespreaded. In the soutern region, far away from Maputo

and from the coast, the very low population density involves almost zero demand in both cases.

3.2 RESULTS

Onsset provides information about the optimum spatial tecnology distribution that minimize the

LCoE, with its related installed capacity and investment requirement.

The stand-alone PV system appears to be a valid solution but, at the same time, it has a very wide

installed cost range (section 2.4.2.2). For this reason, different specific cost are tested, based on local

markets and on african market databese.

Besides, Onsset methodology consists in evaluating the installed capacity starting from the per-

household electricity demand using the capacity factor, which reflects the solar energy potential. This

could appear misleading when we immagine to buy solar devices from local markets, in where, at the

contrary, the electricity demand, as well as the installed capacity, depends on the choosen solar kit

and the PV potential is not taken into account. As a conseguence, two different case are considered,

as explained in section 2.4.2.2.

3.3.1 First case

The stand alone solar solution price is based on Mozambique local solar products, whose price has

been increased to take into accout duties, assistance and quality certification, as illustated in the

section 2.4.2.2. The cost of PV system are set to 102 $ per household for tier 1 consumption and to

1478 $ per household for tier 3 option. The most cost effective technology distribution is presented

below:

Figure 17-Optimal technology distribution in Tier 3-1 (left) and Tier 3-3 (right) scenario

33

In the Tier 3-1 scenario the stand alone PV device is the most cost effective solution for 22.56 milion

of Mozambicans and 10.00 milion people can benefit of the connection to the national grid. The grid

extention seems to be the best solution for only urban household, that require an higher electricity

demand and that are relatively closed to the existing or planned transmission network.

On the other hand, in the Tier 3-3 scenario the higher electricity demand leads to a wider grid

extension. In this case only 1.03 milion people benefit of electricity by means of stand alone solar

devices and the 68.1% of new grid connections are located in rural areas.

In both cases the hydropower mini-grid seems to be the best solution for aproxinately 150,000

Mozambicans, with a different dispersion in the two scenarios. In the first case 15 cells are classified

as MG hydro connected (2.42 MW of average installed capacity) and they are all located in urban

areas.

Differently, in the Tier 3-3 scenario hydropower mini-grids seem to be more widespread and smaller

sized (79 cells with 62 kW of average installed capacity), the majority of which (88.6 %) are located in

rural regions.

The 25% of the stand alone solar solutions is located within 20 Km from the existing or planned

transmission network and it regards low density population area, in which extend the grid would not

be convenient.

In fact, low demand decreases the competitiveness of Mini-Grid and Grid investments, as higher

LCOE’s are required to recover fixed costs of distribution infrastructure. As a conseguence, more

Stand-Alone technology solutions are required to reach 100% access in areas rural areas with low

population density.

The maximum LCoE are 0.773 $/kWh and 0.819 $/kWh and they are both dictated by the stand-alone

solar solution. In the Tier 3-1 scenario the maximum grid LCoE is estimated to 0.402 $/Kwh and the

its marginal cost is not enough to outpace the solar device solution.

Figure 18-LCoE distribution in tier 3-1 (left) and tier 3-3 (right) scenario

34

In the Tier 3-3 scenario the maximum LCoE is higher but less scattered all over the country and it

contributes to lower the average LCoE from 0.755 $/kWh of the Tier 1-3 scenario to 0.609 $/kWh.

It sould be noted that solar stand-alone LCoE’s are fixed in the two scenarios, unlike the next case in

which it depends on the capacity factor. On the other hand, grid LCoE’s incresing with the distance

from the existing or planned transmission network.

With a discount rate of 7% the investmets required to reach the 100% electrification goal are 2.14 B$

and 9.58 B$ respectively for Tier 3-1 and Tier 3-3 scenarios. The majority of these is intended for the

grid extention (74.8 % and 95.9%), which recording an average of 1045 and 1429 $ per new grid-

connected household in the two scenarios. The hydro mini-grid per connection investment is

estimates at 946 $ in the first scenario and 1195 $ in the second one.

35

3.3.2 Second case

In this case the stand alone solar system cost is set to the african average of PV sub-1kW installations,

as illustrated in the section 2.4.2.2.

In the Tier 3-1 scenario the tecnology distribution seems to remain unchanged with respect the

previous case. Still 22.56 milion people is electrified by means of solar home systems, the vast

majority of which is located in rural areas.

In the Tier 3-3 scenario aproximately 231,000 Mozambicans make use of stand alone solar systems,

about one-fifth compared the the previous case. Due to higher solar solution cost, the grid extention

turns out to be the most suitable choice even for sites futher away from the transmission network.

As a result, only 16% of stand alone solution is located within 20 km from the existing or planned grid,

concentrated for the majority in the southern and northern low-populated regions.

The hydropower mini-grid seems not to be affected by the different PV specific cost and still about

150,000 mozambicans make use of this connection approach.

Figure 19-Optimum technology distribution in Tier 3-1 (left) and Tier 3-3 (right) scenario

36

Even in this case the maximum LCoEs (1.654 $/kWh and 1,446 $/kWh) are dictated by the solar

systems and they appear to be much higher, due to the specif PV cost. Unlike the first case, the stand

alone LCoE is not fixed but depends also on the cell solar potential and particular high prices are

observed in the south region, where the irradiance is lower (figure 8).

In the Tier 3-1 scenario the maximum LCoE of the grid-connected solution (0.402 $/kWh) presents a

gap with respect to the minimun stand alone PV LCoE (1.283 $/kWh), while there is not discontinuity

in the Tier 3-3 scenario. As expected, the average LCoE is strongly influenced by the diffusion of stand

alone solution and it is estimated at 1.398 $/kWh for the Tier 3-1 scenario and at 0.732 $/kWh for

the Tier 3-3 scenario.

With a discount rate of 7% the investmets required to reach the 100% electrification goal are 2.58 B$

and 10.09 B$ respectively for Tier 3-1 and Tier 3-3 scenarios. Like the previous case, the majority of

these is intended for the grid extention (62.0 % and 98.3 %). The average grid-connection cost is 1045

$ per household in the first sceanrio (like the first case) and 1501 $ per household in the tier 3-3

scenario (slighly higher due to a more extended grid diffision).

The average investment in solar stand-alone systems is estimated to 184 $ and 2272 $ per household,

which are much higher than the local markets based price. For the hydro mini-grid, instead, it is

practically the same as the previous case.

As exposed in section 2.4.2.2, the african solar home system cost vary in a very wide range and it

would be intresting to figure out how the PV specific cost impacts on the final major outputs.

Figure 20-LCoE distribution in tier 3-1 (left) and tier 3-3 (right) scenario

37

In the Tier 3-1 scenario even the lowest stand alone specific cost (4000 $/kW) is not enough to

differently allocate the population, that is still dived in 22.56 milion with the solar PV tecnology, 18.52

milion grid connected and 0.15 milion with the hydropower mini-grid solution. The figure 18 shows that the grid LCoE range is fixed with respect to the PV specific cost and it does

not overlap the stand alone LCoE range. The reason behind this is that the rural consumption is

anyway too low to promote the grid extention, even if the household is very close the transmission

network. With specific cost lower than 4000 $/kW the stand alone PV system would replace the grid

technology, starting from the grid connected cell that are more distant from the transmission

network.

The behaivor is different in the tier 3-3 scenario, in which the higher rural demand makes more

feasible the grid extention solution. The stand alone cost, in fact, affects the number of Mozambican

that can benifit of electrification by means of such solution.

As expected, the population electrified with stand alone solar devices decreases with the specific cost

of the solar installations. In particular, there are about 4 milion people located near the transmission

network, which can be easily grid connected when the stand alone specific cost increase from 4000

$/kW to 6000 $/kW.

Figure 21-grid LCoE range (purple) and SA PV LCoE range (yellow)

38

In the Tier 3-1 scenario the average LCoE increase linearly with the stand alone PV specific cost, while

in the second scenario the diffusion of the grid solution and the higher demand make the increase

less pronounced.

As happened earlier, the investment cost is dominated by the grid exention. In the high demand

scenario it has higher incidence and it helps to mitigate the incresing stand-alone specific cost,

stabilizing the total investment at aproximtely 14 bilion $. In the tier 3-1 scenario, at the contrary,

expenditure in grid exention remains constant and the overall investment increases with specific PV

cost

Figure 22-Changes in SA PV distribution, when SA PV cost is 14 $/W, 10 $/W and 4 $/W

Figure 23-Average LCoE as a function of SA PV cost

39

The figure 25 shows the trends of the per-household connection cost for the two scenarios and for

the two main tecnologies. It can be said that the stand alone connection cost used in the first case

(on the base of solar market pre-set kits and without considering the capacity factor) corresponds to

an equivalent cost of 6000-8000 $/KW, using the conventional OnSSET methodology.

Figure 24-investment cost

Figura 25-per household investment

40

4. ADDING THE PUMPING ENERGY FOR GROUNDWATER IRRIGATION

In this chapter it is evaluated the electricity demand required to lift the irrigation groundwater in a

particular scenario in which agricultural intensification is praticed without occuring in deplention of

water resources (yield-gap closure scenario).

4.1 Groundwater for irrigation

From 1950 to 2000 the global demand for irrigation groundwater has increased from 100-150 km3 to

950-1000 km3, but, as figure 26 shows, Africa still make a little use of it.

It is widely recognised that economical growth starts from the agricultural sector, and in the near

past so it was for many developing countries, such as India, China and Pakistan.

These economies have drawn support from the exploitation of groundwater resources to increase

the croplands yield and reduce the cost of irrigation. The same process is desiderable in sub-Saharian

african countries, in which agriculture is the driving sector but the scarse use of modern irrigation

techniques results in a very low productivity.

Most of these countries are experiencing ‘economic water scarcity’ due to lack of infrastructure

investment, rather than ‘water resource scarcity’, as reflected by the recognised high groundwater

potential. This means that the main issue related to the groundwater development in Sub-Saharan

Africa is the high cost of water-well construction, mainly due to inappropriate well design and

construction.

As a result, in Africa only about 1% (14 % in Asia) of the cultivated land makes use of groudwater.

Figura 26-areas equipped for groundwater irrigation as percentage of the area equipped for irrigation (AQUASTAT)

41

4.2 The yield-gap closure scenario

In the near future african agriculture have to face four important challanges:

-enhance the production to feed the increasing population.

-generate job in order to contribute to reduce poverty, especially in developing countries.

-manage the water resources in a sustainable way.

-face climate changes

African population is quickly growing (projected 2.6%/year in the next 30 years) and it is becoming

even more important to find a way to ensure food security without causing irreperable environmental

impacts. Food production is one the most water-intensive human activities (it takes about 1 litre of

water to produce 1 Cal of food energy, 3000-5000 litres per 1 Kg of rise), resultifng in the fact that

water use grows at almost twice (1.7) the rate of population increase.

Climate changes will rapresent a further issue, altering rainfall patterns and affecting the availability

and quality of both surface and groundwater. Warmer temperatures could benefit some areas, but

negatively effect others, resulting in an overall negative impacts. Climate changes, moreover, could

particulary bear down on smallholders, which are the backbone of the african agricultural sector.

In this context, increasing the productivity of croplands by means of agricultural intesification is not

an option.

Agricultural intensification is a practice whose goal is to achieve the so called “yield-gap closure”.

This term refers to the difference between a crop’s maximum potential yield and real yield, expressed

as the amount of produced food per cultivated hectare. The maximun potential yield is defined as

the maximum yield of a crop grown in an environment in which is perfectly adapted, with non-limiting

water and nutrients supplies and without occurences of diseases. On average, the World’s most

significant crops (soybean and wheat) produce less than 50% of their maximum potential yield.

Figure 27-current irrigated areas (left) and water scarsity (right), expressed as the excess of water demand over availabe supply (AQUASTATS, Food and agriculture Organization of the United Nations)

42

These conditions cannot be obtained unless modern agricultural techniques are practiced. One of

them is the irrigation, which is well-consolidated in developed countries, but it is still at an early stage

in most of the sub-Saharian Africa. As figure 27 shows, in fact, irrigation is quite diffused in Egypt,

Sudan, Morocco and South-Africa, countries that are all experiencing water scarsity.

The Polito’s Hydrology Department has developed a GIS dataset that shows the amount of irrigation

groundwater demand needed in the yield-gap closure scenario, in such a way that in each cell the

withdrawal is lower than the water renewal. The required water for irrigation is calculated as the

product of the fresh water requirement of a certain cropland and its respective irrigated area. The

first value is the amount of water needed to satisfy the crop evaporative demand, substracting the

contribution of precipitations and considering the change in soil water storage. It is then coupled with

the local recharge groundwater potential, obtained by hydrological models.

The closure gap scenario accounts for both agricultural intensification in already cultivated lands and

for exent of irrigation in raindfed croplands. In areas in which precipitaion are enough to support

agricultural intensification the irrigation is not needed.

Accoriding to the figure 28, the African groundwater for irrigation would increase from 27.4 km3/y to

99.3 km3/y, with the major contribution from the sub-Saharian countries.

As is clear from the figure 28, there is an impressive exension of irrigation in the great majority of

sub-Saharian countries. The current groundwater withdrawal is higher in Morocco, South-Africa and

Nigeria, as also figure 29 shows. The agricultural intensification will promote a great development of

grounwater irrigation in country that makes a little of use of it. For instance, Congo irrigation demand

Figure 28 groundwater demand in current (red) and yield-gap clousre scenario (blue), POLITO Hydrology Department

43

will increase more than 6000 times, while Egypt, which makes already a large use of irrigation, cannot

furher increase it without occuring in water resource deplention.

The Mozambique groudwater demand will increase from 19.6 Mm3/y to 1165 Mm3/y (very close to

the current overall irrigation demand), with a particular demand extension in the northern areas of

the country. There is a region, in the south, where croplands are adeguately fed by precipitations and

the increase of the irrigation water demand would not be rewarding.

As expected, the majority of the demand is requered in rural areas and aproximately 30% of the

overall irrigation water requirement is located more than 50 Km away from the existing or planned

transmission network.

Figure 29-Current and yield-gap closure groundwater withdrawal (POLITO Hydrology Department)

Figure 30-Mozambique current (left) and yield-gap closure (right) groundwater demand for irrigation

44

4.3 Energy demand

Electricity demand required to pump up the groundwater is evaluated according to the formula:

𝑬 =ϒ ∗ 𝑮𝑾 ∗ 𝑮𝑾𝑫

𝜼

Where:

η= electrical efficiency, set to 0.75

ϒ=water specific gravity (9810 N/m3)

GW = per cell groundwater demand (m3/y)

GWD = per cell average groundwater storage depth (m)

The depth of the groundwater depends on the cell location and it is modelled using an empirical

rules-based approach, according to rainfall and aquifer type, as well as proximity to rivers:

Figure 31-Average per cell groundwater depth (POLITO Hydrology Depertment)

45

With this assumptions the addictional energy demands due to ground water lifting results is shown

in figure 32:

The electricity demand results to be 1.029 GWh/y for the 20% scenario and 53.84 GWh/y for the

100% scenario. The demand distribution is vet different between the two scenarios, as well as the

peask demand (11 MWh/cell and 127 MWh/cell).

As shown in figure 32, the relatively shallow depth of the northern region compensates for the high

groundwater demand, resulting in a not extreme energy requirement. On the other hand, the

combination of high water demand with high aquifer depth leads to remarkable electricity demand

in several sites of the southern areas.

The electricity demand seems to be far away from urban areas, in low-populated areas, far away from

the existing or planned transmission network. In particular:

Table 8-additional electricity demand as a function of distance from the grid

In the yield-gap closure scenario 96.7 % of the pumping energy demand comes from rural areas, 55.8

% from sites more than 20 km away from the existing or planned transimission network. Including

the fact the most of the southern demand is located in very low-populated areas, it could cause a

significant change in the most cost effective techology distribution. This is surprending if we consider

rural <5 km 5-10 Km 10-20 km 20-50 km >50 km

Closure yield-gap (GWh/y) 52.11 6.48 5.94 10.36 18.00 13.06

Current (GWh/y) 0.87 0.49 0.28 0.16 0.07 0.02

Figure 32-electricity required to lift groundwater in the yield-gap closure scenario (right) and current scenario (left)

46

that the addictional electricity corresponds to to 4.1% of residential demand in the Tier 3-1 scenario

and to the 1.6% in the Tier 3-3 scenario. This demonstates that even a very low demand increase can

lead to a radical change in best solution choice and investment.

47

4.4 Results

In this section the results of OnSSET are discussed, assuming that the electricity to pump-up the

groundwater is equally distributed in cell households, which reflects the small-scale agricultural

structure of Mozambique. As said before, the introduction of groundwater irrigation schemes could

lead to the diffusion of more-commercial activities, but in this study such possibility will not be

considered. Since the electricity demand in the current scenario does not cause any relevant changes

in the OnSSET outputs, only the yield-gap closure scenario is considered.

In accordance with the chapter 3, two cases will be considered in each scenario: the Tier 3-1 scenario

and the Tier 3-3 scenario. They differ in the rural consumption, which is higher in the second one. In

this case only the conventional OnSSET methodology will be proposed, because the addictional

electricity demand is not uniformely distributed in rural population and it is not possible to assign a

specific solar kit for each energy consumption level. By the way, the entire PV specific cost range will

be explored and one can keep in mind that, as resulted from the previous chapter, solat kit price can

be identified in the 6000-8000 $/kW cost range.

All the addictional irragation water is lifted from underground, resulting in sgnificant diffusion of mini-

grids (both solar and hydro), where peak of electricity demand occur. In the figure below the

technology distribution which minimize the LCoE’s is presented:

In the same way as the previous results, the stand-alone PV solution is visibly more widespread when

rural houesolds electrical consumption is set to 30 kWh/y and it is widely replaced by the grid

extension when the rural consumption is brought to the urban level (410 kWh/y). In this case,

however, one can notice the precence of a forth technology: the solar based mini-grid.

Figure 33-most cost effective technology distribution

48

This solution seems to be the best choice in cells with low population density and especially where

high groundwater irrigation is needed. In fact, in the Tier 3-1 scenario, depiste only 159,000

mozambicans are electrified by means of PV mini-grid, it provide aproximately 26.5 % of the overall

pumping electricity demand. This values decrese to 74,300 and 22.1 % in the Tier 3-3 scenario.

And 77.6 % (Tier 3-1) and 87.7 % (Tier 3-3) of new PV mini-grid connections are located in the rural

southern areas. The table below shows the distribution with distance from the existing or planned

network:

Table 9-Pv mini-grid new household connections

It is interesting to notice that also hydropower mini-grids benefit from the new electricity demand

distribution, recording 43,800 (Tier 3-1) and 99,600 (Tier 3-3) extra connections with respect to the

chapter 2 analysis. The grid connected population remain unchanged in the Tier 3-1 scenario (18.52

milion) and counts for 40.71 milions in the other scenario (150,000 people less with respect the only-

residential demand case). This means that in few cells mini-grids are prefereble to the connection to

the national grid, but in most of the cases they replace stand-alone solutions.

PV mini-grid new connections (thousands of households)

<5 Km 5-10 Km 10-20 km >20 km

Tier 3-1 7.8 3.0 4.8 24.5

Tier 3-3 1.8 1.7 3.0 10.3

Figure 34-LCoE's distribution

49

The pumping electricity demand and the conseguent mini-grid solution contribute to lower the local

LCoE, especially in the south region where low irradiance tends to make it higher. In the Tier 3-1 the

average LCoE is 1.384 $/KWh (without irrigation it is 1.398 $/KWh).

In the high rural residential demand scenario the average LCoE results to be 0.720 $/KWh (0.732

$/KWh without irrigation).

For the Tier 3-1 scenario the overall investment required results to be 2.93 B$, higher whith respect

to only residential demand case (due to the higher stand-alone PV installed capacity). In the other

scenario, instead, it is almost unchanged (10.19 B$).

Table 10-investment share for the various technologies

In the 117 M$ and 102 M$ are intended to solar mini-grid respectively in Tier 3-1 scenario and Tier

3-3 scenario. The investment cost per household result are summarized in the table below:

Table 11-per household average investment cost

The cost of PV stand-alone and grid connection remains almost unchanged with respect to the case

in which only residential demand is considered. The high solar mini-grid cost is due to the higher

installed capacity which, in turn, reflects the addictional power required for the groundwater lifting.

By the way the minigrid investment cost result to be 12680 $/kW (Tier 3-1) and 11037 $/kW (Tier 3-

3), that are considerable higher that the reference price of 8362 $/kW assumed in sectiom 2.4.2.2.

This means that distribution cost turn out to higher than the African average for this kind of techology.

per household connection cost ($)

grid PV SA MG PV MG Hydro

Tier 3-1 1046 229 3094 1052

Tier 3-3 1498 2590 7086 1649

50

Table 12-per household average installed capacity

The higher per-household installed capacities of PV mini-grid are due to their remarkable electrity

demands, that are on average 420 kWh/y in the Tier 3-1 scenario (with respect to the residential 30

kWh/y) and 1106 kWh/y (410 of which for residential purpose). Besides, the majority of PV mini-grid

new connections are located in the southern Mozambique, in which the solar potential is lower.

It should be noted that a uniform increase of the demand leads to the grid exention. In this case,

instaed, there are few demand peaks in sites with a very low population density. The results is that

in such cases mini-grid seems to be a better choice because the building of HV/MV lines,

transformers, as well as network upstream renforcement, would not be rewarded by the low number

of new connection, even if the household demand is relatively high. If the peak is more marked with

respect to the uniform residential load, the solar PV mini-grid diffusion is wider. That is the case of

the Tier 3-1 scenario.

As explained before, the specific cost of the stand-alone PV system is a very uncertain value, due to

the particular sub-Saharian changeble and varied situation. For this reason, different PV cost are

tested and the outputs are compared.

it can be said that in both the scenarios the increasing PV specifc price makes room for mini-grids

solutions, which did not happend in the absence of the addictional pumping electricity demand. In

fact, in the previous case the number of new connections by means of hydropower mini-grid is

constant (150,000) and independent from the stand-alone specific cost. In this case, instead, it is

possible to note a displancement of the solar stand-alone systems, which are substituted by solar and

hydropower mini-grids.

per household average installed power (W)

grid PV SA MG PV MG Hydro

Tier 3-1 93 20 244 121

Tier 3-3 95 259 642 146

Figure 35-mini-grid population and investments cost as a function of stand-alone cost

51

In figure 36 the diffusion of mini-grid for two different stand-alone cost (6000 $/kW and 14000 $/kW)

is illustred. The number of people connected by means of hydropower seems to be much higher in

the 3-3 scenario than what it is. This is due the fact that in tier 3-3 scenario the hydropower mini-grid

are suitable in very low populated area.

In the high rural demand scenario the grid-connection takes on part of the solar stand-alone

displacement, while in the Tier 3-1 scenario the grid exension remains unchanged and whole PV stand

alone reduction is covered by mini-grids, resulting in a considerable diffusion of them.

Figure 36-mini-grid distribution for PV cost of 6000 $/KW and 14000 $/KW, in Tier 3-1 (left) and Tier 3-3 (rigth) scenario

52

Like the case of only residential demand, higher consuptions lead to lower LCoE’s and grid exension

contributes to offset the LCoE increase in the Tier 3-3 scenario.

The investment cost trend for household connection in show in the figure below:

With higher stand-alone specific cost the solar-PV solution become more suitable also for household

with a lower electricity demand, resulting in smaller-sized systems. That is the reason behind the

decreasing of the per-household investment cost, that is accompanied with an increasing of per-kW

specific cost (from 8000 to 15000 $/kW).

Figure 37-average LCoE as a function of PV stand-alone cost

Figure 38-per household investment cost and installed capacity, as a function of PV stand alone cost

53

5. CONCLUSIONS

GIS analysis is crucial in order to make a first assesment and to figure out how and where resources

have to be channeled. Of course its functionality is limited by several factors:

• Inaccuraties of the input data. As shown in the study, a big number of GIS and non-GIS

information have to be provided to the model. These data are often extrapolated from a

varied and not stabilized context. Moreover they refer to the short/medium period, which

increases the possibility that the model departs from reality. In this study the issue of the solar

home systems price has been treated and it has been shown how different specific prices can

effect the analysis outputs. For sure, due to the important role of the grid exension, cost of

LV/MV/HV, transformers and other devices should be further analysed but, at the moment,

the only way seems refering to similar studies in similar regions.

• Inaccuraties of the model. OnSSET is large-scale simulation tool and its aim is to provide a first

idea of how and how much it would cost to electrify an entire country, assigning a certain

consumption level to rural and urban population. The most crucial aspects are the calibration

of the settlement table and the grid exension algorithm, as explained in the section 2.2. It do

not consider the non-residential electricity demand, which could deeply effect the simulation

output. Other limitations are listed in section 2.2.

Nevertheless, it is still possible to arrive at important conlcusions:

• The grid exension plays a very important role in the electrification process, especially when

the electricity demand from rural households is significant. In fact, it is easy to understand

that for cunsumption of the order of 30 kWh/y (the amount of energy consumed by an italian

4 people household in a few days) the grid connection is not an option and smaller-scale

stand-alone or mini grid sysems are preferable, even if their specific cost is extraordinarily

high. On the other hand, when consumptions are higher (but still not comparable with OECD

levels) the grid connection become competive with the other technologies, whose cost can

strongly effect the exension of the national grid. It has to be said that grid exension electricity

is considered as good as the other systems can offer but this is not the case in many devolping

countries, in which power generation and distribution is very unreliable.

It is likely that, even for higher consumption levels, stand-alone systems or mini-grids based

on renewable sources would remain the best choice in remote and low populated rural areas.

• Mozambique’s groundwater recharge potential is more than ten times higher than the

country overall 2017 water demand. It also has one of the largest amount of arable lands in

south-eastern Africa and great commercial potential, thanks to the proximity to ocean and to

five strong neighbouring markets. Groundwater irrigation could rapresent a key factor in

order to ensure food security to its increasing population and, at the same time, to promote

economical growth.

The focus has been on the electricity required to lift the groundwater for irrigation in a

particular scenario in which 100% energy access is achieved and agricultural intensification is

practised. It has been shown that pumping electricity is a small fraction of the residential

consumption (from 1.6% to 4.1%, depending on the scenario).

54

Nevertheless, its distribution (mostly located in rural areas with very low population density

and far away from the national grid) promote the diffusion of hydro and solar mini-grids.

The majority of new mini-grid connections raplace the too expensive solar home systems in

sites where there is a peak demand due to goundwater withdrawal.

As said before, the addictional electricity is relatively low and it is just a portion of the

electricity required for the whole irrigation process. Despite this, it is sufficient, to strongly

alter the technology distribution, promoting mini-grids and the intensification of rural and

isolated peak demand would likely reinforce the validity of such solution.

55

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